Research On Dynamic Vehicle Routing Problem Of Driver-less Cart For Baggage Transportation In Civil Aviation Airport

With the development of commercial aviation,the pressure on passenger transport and freight in airport hubs is increasing year by year,which brings huge costs of ground transportation and the challenge of maintaining service quality under high transportation intensity.The baggage transportation system as an important component of the ground transportation system in civil airports,which affects the operation costs and service quality of the whole airport.Therefore,it is significant to develop a scientific and logical baggage scheduling strategy.However,most of present airports still rely on traditional manual decision-making methods on baggage transportation vehicles scheduling.And the existing studies generally focus on the scheduling optimization of baggage transportation vehicles in static environments,but do not discuss the dynamic baggage transportation in actual airport scenarios.At the same time,using unmanned electric vehicles as baggage carriers,the vehicle battery capacity will have load capacity and distance restrictions,and the vehicle charging and discharging process is accompanied with battery loss,and improper vehicle call will accelerate the decay process,thus accelerating the vehicle battery obsolescence and increasing the battery replacement cost,so the existing model without considering the battery characteristics of electric vehicles can hardly meet the optimization of minimizing operating costs.Therefore,the existing models that do not consider the battery characteristics of electric vehicles can hardly meet the optimization requirements of minimizing the operating costs.In order to solve the above problems,this thesis analyzes the dynamic baggage transportation in airports,constructs the dynamic transportation model of electric baggage transportation vehicles and the corresponding solution algorithm,enables the intelligent transportation decision system to make timely response to the flight information randomly generated and updated during the task,unmanned dispatching of baggage transportation vehicles,considers the battery capacity constraint,reduces the battery loss during vehicle transportation,and achieves the goal of minimizing the total cost of transportation.In summary,the main research contents of this thesis are as follows.(1)For the problem of dynamic transportation process of airport baggage based on unmanned electric vehicle distribution,this thesis proposes the model of dynamic vehicle problem of unmanned baggage transportation in civil aviation airport with load and power constraints,and uses genetic algorithm to solve the model in the static stage of the problem.In the dynamic stage,the degree of impact of the change of the subsequent delivery route of each vehicle on its transportation cost and service quality of the subsequent node at the time of flight demand update is measured,and vehicle rescheduling is carried out based on this.Finally,the feasibility of the solution method is verified through arithmetic experiments.(2)In order to reduce the battery loss of vehicles in the baggage transportation process,this thesis proposes an optimization model for the dynamic path problem of unmanned electric baggage transportation vehicles in civil aviation airports considering battery loss.In the static optimization stage,the battery capacity decay process is quantified as the battery loss cost,a new objective function and constraints are constructed,and the solution is based on genetic algorithm.In the dynamic optimization stage,the Bi-Ele Att-GRU neural network with attention mechanism is introduced to predict the vehicle battery SOC,and a new penalty mechanism and dynamic vehicle path update algorithm are designed based on its prediction results to realize the dynamic vehicle scheduling containing the optimization objective of minimizing battery loss.Finally,experimental validation is performed to compare the experimental results with the model without considering battery loss.The results show that considering battery loss can reduce the total cost of airport baggage transportation.